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[C-Cogn-S]: Computational Cognitive Systems (non-A.I. & A.I.)
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 C-Cogn-S: Computational Cognitive Systems

(non-A.I. & A.I.) [⋆⋆⋆⋆⋆⋆⋆] 

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Animal/Human + non-A.I. computer/machine + A.I. computer/machine

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The term 'Cognitive' here refers to either the human user's own cognition interacting with a computer program and learning from it; or it can refer to an 'intelligent program' which may or may not use A.I. (Artificial Intelligence, strong general-purpose AI --- ie. DML, deep machine learning).

 

 

Android App #1 (Java) – 'Flying Neural Net' Basic non-AI 2D Game

 

 

The link to my Google Play Account where you can download my published Android Apps:

 

 

https://play.google.com/store/apps/developer?id=BNT+AppLab+%28Multidisc+Neurosci+Tech+Ltd%29

 

https://play.google.com/store/apps/details?id=com.hmproject004gam2jan.hm009949.myapplicationgam2jan&hl=en

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https://developer.android.com/distribute/console/index.html
Developer Console


 

 

Project Fields:​ 2D Games Development & Design

Description: xxxxx

My Work & Contributions: Coded all from sctratch – 5000 lines of code +

Collaborations/Feedback: xxxxx

Location Activities: Home-based

Status/Timeline:

Started: Sept 2016

Most Research Done: Jan 2017

Self-testing done: April 2017

Published to Beta testing: May 2017

Late 2017: Full Production

2018+: Monetization revenue (TBC)

 

Other Links to external sources:

--- JDK 8.0 JRESE https://java.com/en/download/win10.jsp

--- https://developer.android.com/studio/index.html   

--- https://android.stackexchange.com/

--- https://github.com/tensorflow/tensorboard

--- www.cocos2d-x.org/ Cocos2d-x Open-Source Game Development Platform

--- https://www.gamedev.net

--- https://docs.unity3d.com/Manual/index.html

--- www.androidauthority.com

 

--- https://github.com/Harry-Muzart

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Hardware: Intel Quad Core i7 & Celeron Computers; Android Acer Tablet; Phone

Operating Programs & Software Tools: MS Win 10 OS;  Android OS; Android Studio 2.3, Eclipse.

Programming Languages: Java & XML (but C++ could be used for native)

Coding Elements:  OnClickL; ShPrefs (AdMob); Java 7.0 and AS (.jva, .xml, gradle build)

Computational Techniques: xxxxxxxxxx

 

Link to Programming Code Files:

Public (full open access) (Google Drive Cloud and GitHub): https://drive.google.com/drive/folders/0B0qSKFqszohLTTZIZkg1c09xaVU?usp=sharing

Private (shared password-protected) (Google Drive Cloud): XXXXX

File types: xxxxx

​License: xxxxx

 

 

Android Studio Project (Blank)

--- MyApplication14oct2017 >

 

1595 files (665 subfolders) 39.4 MB

app > src > main > res > layout

activity_main_activity1a7b.xml 1 KB

app > src > main > java > com > example > harrymuzart > myapplication14oct2017 >

MainActivity1a7b.java

 

app > src > main

AndroidManifest.xml

build.gradle

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Base Math Coding & Program Computations & System (Diagrammatic):

See Image below

 

Images below: Content Files by Me, Screenshots by Me.

 

Video Embeds below: see my YouTube channel.

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For other Pics/Vids, see:

https://photos.app.goo.gl/UK6yX8SSnARWdJjw6

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Android App 1 - Game (psyc)
GO!

...

Actual App:

TBC:

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Other Android Apps – In development:

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--- Flying Neural Net (Basic Game) 1.0 (see above)

--- Neuroscience (Interdisciplinary) eLearning Quizzes [TBC]

--- Digital Health Data social app (like 'Streams' by Google DeepMind Health)

--- A real-time image object classier (using ML like https://github.com/llSourcell/YOLO_Object_Detection) using Android camera, which can then be used for other purposes.

--- Psychiatry patients CBT App (Like SloMo by KCL IoPPN, also others by UCL ICN and Imperial)

--- A Mediation/Mindfulness App (based on literature in audio-visual-tactile cogn neurosci), similar to much already on the market.

--- A brain-training IQ-test-like App

--- Interactive Brain Connectomics & 3D Rotations (like by CSH Labs and Allen Institute)

--- RSS Reader & News Feed

--- Social Feed

--- UCL Navigational Map App

 

[Images and videos available for each of the above.]

 

 

​--- (*) Cognitive Sciences, Cognitive Behaviour, eLearning, Games, Game Theory Mechanics, Communications, HCI, Educ., Graphical 3D models  {Cognition & Interactive Comms}

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Computational & Cognitive Neuroscience relevancy:

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About CN In terms of content

 ---CN Comput

 ---N Cognitive

 ---N

 

 How built - CN In terms of applications

 ---CN Computational Neuroscience: Base Coding for Intelligent Systems

 ---Neurobiol Labs - hands-on end-user applications in ucl/nhs

 ---Cognitive Neuroscience: Design and Management

 

End user CN

 ---CN

 ---N Physical Integration

 ---N

My Other Android Apps
Windows Phone App

Windows Phone App

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*** NeuroCogFeeds (App by HM)

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(some accessibility discontinued)

 

App Developed (Windows 8 Phone) (not yet published in Windows App Store)

 

--- This was done using User-Interface App Development in Visual Studio, not actual programming (which would’ve been C++/C#/.NET/VisBASIC/Obj-C in this case)

 

--- Human-Computer Interaction leading to eLearning (learning by interaction and visualization).

--- This app is different from other platforms because:

          (a) you do not need to access each feed manually, it would save people a lot of time (and the next app version will feature about 100 more feed lists).

          and (b) the app does not depend on an internet connection, nor do the archived feeds, only the newest data depends on an internet connection; also, if one website has a server problem, it will not affect other parts of the app.

 

https://drive.google.com/drive/folders/0B0qSKFqszohLTTZIZkg1c09xaVU?usp=sharing

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https://github.com/Harry-Muzart  > //hm_proj_002#//

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https://developer.microsoft.com/en-us/ > https://appstudio.windows.com/en-us/

 

video: youtube TBC

 

https://github.com/Harry-Muzart/hm-project-2/blob/master/NeuroCogFeeds.Shared.shproj

Build Variable Module

 

Other Links to external sources:

https://www.visualstudio.com/vs/

https://developer.microsoft.com/en-us/windows/apps/develop

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Python Project (incl. Basic ML)

Machine Learning (with Python & Extensions)

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*** Python ML Mini-Project 'AlphaMem'

 

Project still being worked on - see GitHub for my (very slow!) progress towards decoding all this

 

My articles:

https://sciarticles.wordpress.com/article-2/  > //latter_part// (in Python v3.0+)

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https://github.com/Harry-Muzart  > //hm_proj_001#// > Jupyter code

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My links to external resources:

https://scientifically.org.uk  > //-2e-comp-neuro-ml// > TensorFlow neural network simulation.

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​https://www.youtube.com/playlist?list=PL3-vVGjXPjaIFCik7cD-6AYmvZNWbNJfh

https://www.youtube.com/playlist?list=PL3-vVGjXPjaKhlqCcMeZMoIsK8RD00bNk

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Images: Content by me, Screenshots by me.

 

 

 

Project Fields:​ xxxxx

Description: xxxxx

My Work & Contributions: xxxxx

Collaborations/Feedback: xxxxx

Location Activities: xxxxx

Status/Timeline: xxxxxx

 

Other Links to external sources:

https://github.com/Harry-Muzart/tensorflow

https://cloud.google.com/ml/

https://www.python.org/downloads/

https://anaconda.org/

https://pypi.python.org/pypi/numpy

https://sebastianraschka.com/deep-learning-resources.html

 

Hardware: Intel Quad Core i7 & Celeron Computers;

Operating Programs & Software Tools: MS Win 10 OS; Python 3.6, Shell, IDLE; Java packages; Tensorflow 1.3

Programming Languages: Python

Coding Elements:  xxxxxx

Computational Techniques: xxxxxxxxxx

 

Link to Programming Code Files:

Public (full open access) (Google Drive Cloud and GitHub): https://drive.google.com/drive/folders/0B0qSKFqszohLTTZIZkg1c09xaVU?usp=sharing

Private (shared password-protected) (Google Drive Cloud): XXXXX

File types: .py

​License: xxxxx

 

--- lib site packages numpy matlib.py (2 KB)

--- 19 py files - testings (20.7KB)

--- MASTER_NN_012.py (16KB)

--- about_MASTER_NN_012_file.txt (1KB)

 

 

Base Coding & Program Computations & System (Diagrammatic):

XXXXXX

 

Images:

Content Files by Me, Screenshots by Me

 

Video Embeds: (video will be made and uploaded soon)

Click here for my Basic Python ML
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DCNNs Object Recogn

Deep Convolution Neural Networks and Object Recognition

 


Also see : https://www.bioneurotech.com/iwa-dml

 


For the links to all the code, see:

https://github.com/Harry-Muzart/harry-muzart.github.io

https://harry-muzart.github.io/

 

This includes work on the video below.


For each frame, the data output looks like this:

[{"label": "person", "confidence": 0.92, "topleft": {"x": 82, "y": 30}, "bottomright": {"x": 733, "y": 525}}, {"label": "tie", "confidence": 0.91, "topleft": {"x": 331, "y": 411}, "bottomright": {"x": 421, "y": 525}}] [{"label": "person", "confidence": 0.92, "topleft": {"x": 82, "y": 30}, "bottomright": {"x": 733, "y": 525}}, {"label": "tie", "confidence": 0.91, "topleft": {"x": 331, "y": 411}, "bottomright": {"x": 421, "y": 525}}] [{"label": "person", "confidence": 0.92, "topleft": {"x": 82, "y": 30}, "bottomright": {"x": 733, "y": 525}}, {"label": "tie", "confidence": 0.91, "topleft": {"x": 331, "y": 411}, "bottomright": {"x": 421, "y": 525}}] [{"label": "person", "confidence": 0.92, "topleft": {"x": 82, "y": 30}, "bottomright": {"x": 733, "y": 525}}, {"label": "tie", "confidence": 0.91, "topleft": {"x": 331, "y": 411}, "bottomright": {"x": 421, "y": 525}}] [{"label": "person", "confidence": 0.92, "topleft": {"x": 82, "y": 30}, "bottomright": {"x": 733, "y": 525}}, {"label": "tie", "confidence": 0.91, "topleft": {"x": 331, "y": 411}, "bottomright": {"x": 421, "y": 525}}] [{"label": "person", "confidence": 0.92, "topleft": {"x": 82, "y": 30}, "bottomright": {"x": 733, "y": 525}}, {"label": "tie", "confidence": 0.91, "topleft": {"x": 331, "y": 411}, "bottomright": {"x": 421, "y": 525}}] [{"label": "person", "confidence": 0.92, "topleft": {"x": 82, "y": 30}, "bottomright": {"x": 733, "y": 525}}, {"label": "tie", "confidence": 0.91, "topleft": {"x": 331, "y": 411}, "bottomright": {"x": 421, "y": 525}}] [{"label": "person", "confidence": 0.92, "topleft": {"x": 82, "y": 30}, "bottomright": {"x": 733, "y": 525}}, {"label": "tie", "confidence": 0.91, "topleft": {"x": 331, "y": 411}, "bottomright": {"x": 421, "y": 525}}] [{"label": "person", "confidence": 0.92, "topleft": {"x": 82, "y": 30}, "bottomright": {"x": 733, "y": 525}}, {"label": "tie", "confidence": 0.91, "topleft": {"x": 331, "y": 411}, "bottomright": {"x": 421, "y": 525}}]

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For a different cloud-supported Matlab version, see:

https://photos.app.goo.gl/UWCuHimwxddnNFZw5

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Reinforcement Learning

Reinforcement Learning

 

 

 

Deep Reinforcement Learning AI (Agent POV) (Backwards Replay of Finding Reward-based Navigation Solutions to 3D Maze)

Video adaptation by Harry Muzart
* THIS VIDEO CONTAINS NO AUDIO

Original Work - Code & Research:

https://deepmind.com/research/
https://github.com/deepmind/lab
https://arxiv.org/abs/1612.03801


https://www.bioneurotech.com
https://github.com/Harry-Muzart

Google DeepMind videos:


Channel: https://www.youtube.com/channel/UCP7j...
Training Environments: https://www.youtube.com/playlist?list...
Lab Nav Maze Lvl 1: https://www.youtube.com/watch?v=M40rN...


 

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MDP_RL (Matlab)

MDP (Markov Decision Processes) and RQL (Reinforcement Q Learning) (in Matlab)

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https://github.com/Harry-Muzart/MDP_RL_HM_model_1x

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ANN agents in grid env with actions A (via transition matrices), and states S, and rewards R; trained over many epochs.

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(not free energy Bayesian model optimization or active inference)

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see:

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https://uk.mathworks.com/products.html?s_tid=gn_ps

https://uk.mathworks.com/help/referencelist.html?type=function&s_tid=CRUX_gn_function

https://uk.mathworks.com/matlabcentral/profile/authors/9089185-harry-muzart

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e-Learning PyGame

Game in Python/Other, using GUI Visual Display (see SourceForge Apps)

 

https://sourceforge.net/u/harry-muzart-01/download-apps/

https://sourceforge.net/u/harry-muzart-01/download-apps/2019/05/datax45654k/

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A 2D game. A basic agent navigates a 2D grid world and need to find rewards pellets and avoid negative items. (Some elements not yet finished)

 

My file:

 

--- Pygame.py (2KB)

 

 

 

External by others:

https://www.pygame.org/wiki/links

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TBC

G Chrome Web Extension

Chrome Extension for ML Analytics linked to User-based Online Databases

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BNT.ext for Chrome

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"BNT Extension" (deployed but doesn't do anything yet, full version TBC).

---1--- G Web App Scripts of Chrome Developer Environment on Windows 10 PC (using JavaScript, HTML5, CSS) ---> Chrome (by Google) Internet Browser *Extensions*, for any OS (G Chrome OS, MS Windows 7+, iOS/Mac, Linux, Other --- for any desktop PC / laptop / tablet / phone). {Internet connection needed}

--- Apps will be about Computational Neuroscience / Machine Learning , and they will aim to be directly use Computational Neuroscience / Machine Learning.

--- App Link - Science Papers Preferences Suggestions Feeds

--- Extensions - Sentiment Analysis of Text and Images

--- Website Tools - Database SQL PHP

 

 

Other Links to external sources:

https://developers.google.com/apps-script/

https://developer.chrome.com/home

 

 

My files:

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--- icon.png 34KB

--- manifest,json 1KB

--- popupBNT.html 2KB

--- popup.js 5KB

app script g ext
git hm

3D Virtual Reality Simulation (in Unity Engine), for Human & AI Spatial Navigation ; + 360 3D Augmented Reality Applications Dev

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Currently being developed:

A 3D simulation similar to the GTA5/Doom game engine framework mods, which is done is Unity 2.0, using Visual Studio on MS Windows, and that will be trainable on machine learning algorithms. This will be used as a test-bed for spatial navigation in first and third person.


 

3D VR Spatial Navigation
2019-05-03 (5)
2019-05-03 (3)
2019-05-03 (4)
2019-05-03 (1)
2019-05-03 (6)
MY OTHER/FUTURE WORK

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For other Interactive 360 3D Virtual Reality, 360 3D Video-Audio Navigation, 360 3D Augmented Reality:

#1 - Testing Existing Programs (e.g. from Google AR).

#2 - Contribute feedback and/or code to those in beta mode.

#3 - Inspirations to building my own.

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https://photos.app.goo.gl/Sf1jFH32AfVGmPD59

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Other

 

 

My Other & Progressing & Future Work, and external, etc.

 

 

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#### My Future Projects (currently being researched) ####

 

--- Web ML with Python and SQLite

--- ML/AI Systems for Varied Applications

--- Cognitive Analytics for Visual Recognition, Language Comprehension, Spatial Predictions

--- Cognitive analytics for visual recognition, language comprehension, spatial predictions

--- Intelligent internet networking social forum

--- Unity3D/Unreal Game, GTA Mod for AI

--- Unity3D/Unreal Mod Game Simulator

--- Visual Anim Graphics Video Programming

--- DeepMind Open-Source lab

--- Prolog for AI

--- Go, Lua and Ruby for AI

--- iOS app using Swift

--- Google Assistant App

--- HCI

 

 

 



Other future works will be related to these other external independent projects by other people/organisations listed below.


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Here is a new list :

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â–º https://sites.google.com/site/bioneurotech/-repo-2
â–º https://docs.google.com/document/d/1Nv6BimGLFgvbSYeNQZO5Cjna_iWcquwoF47MMsll5fA/edit?usp=sharing

Here is a previous list...
 

Also See:

--- StackExchange/GitHub on Google Ai Expt

--- Google AI experiments

https://experiments.withgoogle.com/ai

Also see:

--- http://allpriorart.com/

All Prior Art - An amazing project that uses deep machine learning algorithms in order to attempt to automatically generate innovate ideas and publicly publish all possible new 'prior art' (see https://www.epo.org/learning-events/materials/inventors-handbook/novelty/prior-art.html), thereby making the published concepts not patent-able. The purpose is to democratize ideas, provide an incentive for reform in the US and international patent systems, and to pre-empt patent trolls.

 

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